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cloudml vs maplegend

A side-by-side editorial comparison of cloudml and maplegend — release velocity, themes, recent moves, and the top alternatives to consider.

cloudml vs maplegend: at a glance

Featurecloudmlmaplegend
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesmachine-learning, google-cloud, tensorflow, model-trainingcartography, legends, base-graphics, spatial
Last editorial update45m ago2h ago
WebsiteVisit →Visit →

What is cloudml?

Six years since the last functional change, and Google renamed the service it wraps in the release before that

cloudml lets R users train keras, tfestimators and tensorflow models on Google's managed machine learning service, tune hyperparameters there, and deploy the results. Its last release with functional content was 0.6.1 in September 2019, which adapted to Google renaming the service from ml-engine to ai-platform. The only entry since is a 2025 documentation update made to satisfy CRAN.

Read the full cloudml trajectory →

What is maplegend?

The legend engine mapsf spun out, now covering legend types the parent map package can draw.

maplegend draws the legends for base-R thematic maps, extracted from mapsf so both packages could evolve the legend vocabulary independently. It has been catching up to the map types it has to serve: 0.6.0 added choro_point, choro_line, and choro_symb for choropleth legends rendered on circles, lines, and symbols, following the histogram legend type in 0.4.0. Considerable effort has gone into behaving correctly when the plot aspect ratio is not 1, which required refactoring most of the package in 0.4.0 and still produced a proportional-symbol segment sizing fix in 0.6.3.

Read the full maplegend trajectory →

cloudml vs maplegend: editorial side-by-side

C
cloudml
ANALYTICS
0.0

Six years since the last functional change, and Google renamed the service it wraps in the release before that

◆ Current state

cloudml lets R users train keras, tfestimators and tensorflow models on Google's managed machine learning service, tune hyperparameters there, and deploy the results. Its last release with functional content was 0.6.1 in September 2019, which adapted to Google renaming the service from ml-engine to ai-platform. The only entry since is a 2025 documentation update made to satisfy CRAN.

◆ Where it's heading

The visible arc is short and stops abruptly. Releases through 2018 tracked the TensorFlow runtime version and patched packaging problems; 0.6.1 added a customCommands hook so users could run OS-level setup before package installation, and adjusted to the service's new name. Then nothing for six years. A 2025 release containing only documentation changes is the standard signal of a package being kept on CRAN rather than being developed.

◆ Prediction

There is nothing in this feed to support a prediction of functional work. The most likely next event is another CRAN-driven documentation patch, or archival.

M
maplegend
ANALYTICS
0.0

The legend engine mapsf spun out, now covering legend types the parent map package can draw.

◆ Current state

maplegend draws the legends for base-R thematic maps, extracted from mapsf so both packages could evolve the legend vocabulary independently. It has been catching up to the map types it has to serve: 0.6.0 added choro_point, choro_line, and choro_symb for choropleth legends rendered on circles, lines, and symbols, following the histogram legend type in 0.4.0. Considerable effort has gone into behaving correctly when the plot aspect ratio is not 1, which required refactoring most of the package in 0.4.0 and still produced a proportional-symbol segment sizing fix in 0.6.3.

◆ Where it's heading

This is a support library whose backlog is defined by its caller. Every legend type mapsf can produce needs a matching legend renderer, and the release notes are dominated by spacing, offset, and border details — box_cex for symbol spacing, NA box placement in horizontal choropleth legends, text overflow when no_data is set. The shared vocabulary with mapsf is being maintained deliberately, with val_rnd, val_big, and val_dec propagating through legend types release by release. Version numbering is not monotonic in this feed, with 0.4.0 published seconds after 0.5.0.

◆ Prediction

Expect the remaining combined map types to acquire matching legends and the val_* formatting arguments to reach the types that still lack them.

Alternatives to cloudml and maplegend

Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either cloudml or maplegend.

See all cloudml alternatives → · See all maplegend alternatives →

Recent activity from cloudml and maplegend

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 2mo agomaplegendContinuous legend formatting and aspect-ratio segment fix
  2. 4mo agomaplegendChoropleth legends on points, lines and symbols
  3. 7mo agomaplegendPackage-wide refactor for non-unity aspect ratios, histogram legends
  4. 7mo agomaplegendSingle-modality legends allowed for typo, symb and prop_line
  5. 0y agocloudmlDocumentation updated for CRAN
  6. 1y agomaplegendAlpha transparency and redraw on device resize
  7. 1y agomaplegendOffset and symbol sizing aligned with mapsf
  8. 6y agocloudmlai-platform command adopted; custom pre-install commands added
  9. 7y agocloudmlDefault runtime moves to TensorFlow 1.9
  10. 8y agocloudmlPatch for CRAN results and a packrat error
  11. 8y agocloudmlCloud training, GPU jobs, tuning and deployment from R

Frequently asked questions

What is the difference between cloudml and maplegend?

They serve adjacent needs but don't currently overlap on shipped themes. cloudml and maplegend are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is cloudml better than maplegend?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. cloudml and maplegend are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to cloudml?

Top cloudml alternatives in Analytics are ranked by recent ship velocity. Browse the "cloudml alternatives" section above for the current picks, or visit /alternatives/cloudml for the full list with editorial commentary on each.

What are the best alternatives to maplegend?

Top maplegend alternatives in Analytics are ranked by recent ship velocity. Browse the "maplegend alternatives" section above for the current picks, or visit /alternatives/maplegend for the full list with editorial commentary on each.